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Record W4413435870 · doi:10.1017/mdh.2025.10026

Little lives—reading between the lines: insights from the Northampton Infirmary Eighteenth Century Child Admission Database

2025· article· en· W4413435870 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMedical History · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsThe Scarborough HospitalRoche (Canada)University of Toronto
FundersJackman Humanities Institute, University of TorontoUniversity of Cambridge
KeywordsReading (process)World Wide WebComputer scienceData scienceMedicineLibrary scienceDatabasePolitical science

Abstract

fetched live from OpenAlex

The presence of children in eighteenth-century English voluntary hospitals is an area of increasing interest and attention. The Northampton Infirmary admission records detail inpatient and outpatient ages from 1744 to 1804, allowing for longitudinal investigations of children in the institution. The most common distempers affecting children were surgical infections, infectious diseases, and skin diseases; fifty-six per cent of the child patients were male and 43.3 per cent were female. Nearly seventy-five per cent of children left the hospital 'cured'. This article outlines the Northampton Infirmary Eighteenth Century Child Admission Database, and demonstrates how the patterning of distempers within and among children provides insight into the health journeys of eighteenth-century children through the lens of their bodies, their parents, and their institutional recommenders.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.702
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.255
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it